Read our series of interviews with academic, corporate and industry experts on cutting-edge business ideas.

GARY HAMELCo-founder and Director of the Management Lab, Mr. Hamel shares how organizations can respond better to risks and opportunities by engaging with their wider ecosystem.

JULIAN BIRKINSHAWProfessor of Strategic and International Management and Director of the Management Lab at the London Business School, Dr. Birkinshaw shares how businesses can enhance their agility by engaging more effectively with stakeholders.

IOANNIS IOANNOUAssistant Professor of Strategy and Entrepreneurship at London Business School, Dr. Ioannou shares how businesses can enhance their agility by engaging with stakeholders outside the boundaries of the firm.

REBECCA SCHINDLERResearch Leader at RAND Europe
Ms. Schindler shares how the Internet of Things will affect society, business and the economy.

Stitch Fix, an online clothing retailer, provides a glimpse into how some businesses are already making use of AI-based machine learning to partner with employees. This company's success story is about how AI and people work together, with each side focused on its unique strengths.

Many alarms have sounded on the potential for artificial intelligence (AI) technologies to upend the workforce, especially for easy-to-automate jobs. But managers at all levels will have to adapt to the world of smart machines.

As emerging technologies follow a path of accelerating improvements in price and performance, the potential for significant business disruption from outside the familiar world of traditional competitors increases. As a hedge against unpredictable competition, many large companies are embracing a new approach to research and development known as “open innovation.”

Although today’s factories use automated workflows, process change is still mostly manual. However, thanks to machine learning algorithms things are changing rapidly. It's becoming possible for smart software to scrutinize data from a variety of sources and redesign processes in real time.

One of the most human of business activities—sales—is currently undergoing a digital renaissance. Social media, website interactions and A/B tests are providing much more sales-centric data than ever before. To help make sense of all the available data and to improve sales effectiveness and efficiency, organizations are turning to machine learning. Smart machines are becoming trusted sidekicks in sales departments as they make opaque processes more transparent, provide analysis to inform decision making, and offload low-value tasks.

Modern organizations are under pressure to innovate faster than ever and leaders are realizing that going it alone won’t get the job done. Instead, they are seeking to accelerate innovation by collaborating beyond their own boundaries.

Winning in business is often a matter of getting new offerings to market at speed. But in their efforts to collaborate with new partners, many companies are experiencing difficulty maintaining the necessary pace.

The challenges of big firm—small firm collaboration are considerable: Different cultures, Different attitudes about sharing intellectual property, Different concerns about risk sharing, and others. So it’s no simple task to meet the strategic objectives of such partnerships.

How Companies Are Using Machine Learning to Get Faster and More Efficient

Machine-reengineering is a way to automate business processes using machine learning. Although machine-reengineering is new, companies are already seeing striking results with it, particularly in boosts to speed and efficiency.

Our study found that organizations are using machine-reengineering to establish new forms of human-machine collaboration that break through the bottlenecks of complex digital processes. In some cases, such as interpreting images or writing reports, machine-reengineering directly helps workers perform digital tasks. In other cases, machine-reengineering helps people uncover insights that are buried in a mountain of data.

Big companies across sectors are stepping up open-innovation collaborations with small high-tech ones across the world.
A recent Accenture survey of executives at 205 large companies and 201 small high-tech firms based in China, India and the US disclosed key reasons for this growing camaraderie between the Davids and the Goliaths. As much as 92 percent of our survey respondents from the big companies said they believe that open innovation with small high-tech firms helps them accelerate new product development.

Powerful machine-learning algorithms that adapt through experience and evolve in intelligence with exposure to data are driving changes in businesses that would have been impossible to imagine just five years ago. The PCs and databases introduced during the reengineering of the 90s have grown up: the rules-based codes written by engineers are giving way to learning algorithms driven by the machines themselves. As a result, business processes are being machine-reengineered.

Big Bang Disruption authors Paul Nunes and Larry Downes pick the most disruptive innovations at CES 2016 and reflect on whole categories of technologies that, only a few years ago, took their first baby steps at CES and are now occupying entire floors of the show.

As the price and performance of these innovations improve, the number of experimenters proliferates, setting the stage for the often sudden mass adoption that is characteristic of Big Bang market development.

Business academic Clayton M. Christensen’s article in the latest issue of Harvard Business Review tries to turn back the clock on the concept of “disruptive innovation”—back to Christensen’s original definition of a product or service that offers poorer performance than existing goods but which uses new technology that will eventually overcome that of today’s incumbents. But since Christensen’s original research in the 1990's, the nature of technological innovation has changed.

We don’t believe Christensen’s theory is wrong, but it’s only part of the story.

Robotics and other digital innovations are changing how organizations learn. Companies are challenged by changing roles and learning the new skills required in an increasingly digital world. Even as business leaders signal the importance of talent to the overall success of an organization’s digital journey, they express concerns about talent readiness. In an Accenture Strategy survey, 44 percent of business leaders reported "lack of skills" as a key barrier to digital transformation.

Finding an all-encompassing definition of a robot is actually a difficult problem, even for world-class roboticists. Form-factors, intelligence, and the purpose of robots can all vary significantly. And yet many of us think we know a robot when we see one. How is this so?

For decades, screens have been the center of our information world—first with computers and more recently with smartphones and tablets.

But the objects now being embedded with computing power and Internet connectivity don’t all lend themselves to screens and the result will be a host of new screen-free interfaces, driven by voice commands, gesture controls, or simply automated responses to sensor data.

Just like physical inventory risks spoiling or becoming obsolete while stacked in a warehouse, excess marketing inventory—product information and vague brand preferences that sit in customers’ minds—yields few long-term returns.

Marketing organizations can get their surplus production problems under control by embracing just-in-time marketing—a similar approach to just-in-time manufacturing adopted shortly after World War ll. This new way of manufacturing saved companies from drowning in excess inventory as they attempted to capture the benefits of scale while serving too few customers.

The Internet of Things is attracting attention as a new force for growth in some of the world’s poorest countries.

While on the surface of it, a model that uses networks of internet-enabled devices might seem to have limited applicability to the world’s least-developed economies, many elements of the IoT model, such as cheap sensors and wireless technologies, are well suited to conditions in poor countries.

Moreover, the IoT can boost productivity and compensate for poor infrastructure, a barrier to growth in many developing countries.

As is often the case in science-fiction plotlines, it’s unlikely machines will ever spell the fall of mankind. It’s quite possible however, they will enhance and extend the human touch by augmenting our brains and brawn, not replacing them.

Things like virtual sensors, analytics, advanced robotic devices, developments in artificial intelligence, automated virtual assistants, 3-D printers, wearable devices, collaboration software and gaming capabilities have the potential to reshape work practices like never before. Digital technology also makes it so that work can be done from a distance and creates a new level of flexibility on where and how it is done. In this way digital amplifies human capability but does not eliminate the human touch.

As India rapidly moves into the digital era, leading Indian businesses are changing their business models to capture the opportunity.

In a recent Accenture survey of more than 100 Indian senior executives, nine out of ten said “being digital” is a strategic imperative for their companies over the next five years.

That sense of awareness, however, has not necessarily translated into the right strategic focus. Many companies are concentrating on process efficiency but are missing out on real growth. This means developing closer connections with customers and offering new products and services by digitalizing their business models.

The human body interacts with the physical world in subtle and sophisticated ways. But today’s technology can sometimes feel like it’s out of sync with our senses as we peer at small screens, flick and pinch fingers across smooth surfaces, and read tweets “written” by programmer-created bots. These new technologies can increasingly make us feel disembodied.

As people and companies prepare to adapt to the Internet of Things (IoT), with its ever-widening focus on machine-to-machine (M2M) communication, it’s a good time to ask where people will fit in.

Leadership

“Today’s offerings are both better and cheaper right from the start thanks to digital technology, causing Big Bang Disruption in every industry, and putting digital transformation at the top of every company’s strategic agenda.”

"You want insight on how IT impacts the enterprise and organization? Ask the people using it. Ask them how it's improving the way they work and make decisions. Researching digital technology isn't an abstract exercise but begins with grounded questions around what makes people better and their contributions more valuable."

“Digital technology is disrupting every industry, creating markets that are larger, more contestable and more competitive. Only with breakthrough innovation will businesses, governments and the social sector be able to deliver and sustain the benefits of digital transformation.”

“New technologies, globalization and aging populations are changing what it means for nations and businesses to be competitive in the 21st Century. The advantage will fall to those who can creatively seize these shifts for economic renewal and growth.”

"We have an obligation to think big; to explore and inform. Providing evidence-based insights and prescriptions to business leaders, policy makers and civil society is our best chance of generating real socio-economic progress for all."

“Clear writing is the product of clear thinking. We work from the very start to get the ideas right—to ensure they are differentiated, powerful, and practical—and only then do we start writing, revising, revising again, and finally editing.”

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